43 research outputs found
The small molecule 2-phenylethynesulfonamide induces covalent modification of p53
No full textp53 is a tumor suppressor protein which is either lost or inactivated in a large majority of tumors. The small molecule 2-phenylethynesulfonamide (PES) was originally identified as the inhibitor of p53 effects on the mitochondrial death pathway. In this report we demonstrate that p53 protein from PES-treated cells was detected in reduced mobility bands between molecular weights 95–220 kDa. Resolution of p53 aggregates on urea gel was unable to reduce the high molecular weight p53 aggregates, which were shown to be primarily located in the nucleus. Therefore, our data suggest that PES exerts its effects through covalent cross-linking and nuclear retention of p53. [ABSTRACT FROM AUTHOR]Peer reviewedfinal article publishe
Non-canonical sensing mechanisms in bacteria
No full textBacteria continuously experience changing environments. Their ability to sense their local habitat and respond appropriately is essential for their survival. For example, bacteria form biofilms to share nutrients and protect themselves from harmful factors. Or they synchronize their gene expression patterns within the community for optimal performance in response to fluctuations in population density through quorum sensing. Additionally, bacteria have evolved chemosensory navigation machineries to sense chemicals around them and move towards nutrient-rich regions or away from toxins in the process known as chemotaxis.
Chemotaxis has been extensively investigated in number of bacterial species, such as Escherichia coli, Salmonella typhimurium, Pseudomonas aeruginosa, Helicobacter pylori, and Bacillus subtilis. In the past five decades the study of bacterial chemotaxis has been mainly focused on simple molecules, including amino acids and sugars, which are essential for cells growth and survival. Although the details of the underlying molecular basis in chemotaxis vary among bacterial species, they all share a canonical mechanism to sense and respond to these simple molecules. Little is known about chemotaxis to other molecules and the governing sensing mechanisms. In this work, we studied chemotaxis to unconventional molecules in the B. subtilis bacterium and demonstrated the potential molecular mechanisms for sensing these compounds.
Many biological processes are influenced by pH. Therefore, cells have to sense and respond to intracellular and extracellular pH. Chemotaxis to pH has been studied in number of bacterial species. We found that B. subtilis also exhibits chemotaxis to pH. Interestingly, pH chemotaxis is bidirectional in B. subtilis. McpB and its three paralogs, namely McpA, TlpA and TlpB are responsible for pH sensing. We investigated the molecular basis for bipolar pH sensing. Modified capillary assay was used to measure responses to opposite pH gradients. Through in vivo chimeric receptor and site-directed mutagenesis studies, we found that the lower regions of the extracellular ligand binding domains of the chemoreceptors are involved in pH sensing. In particular, we identified number of key amino acid residues that define the polarity of pH sensing.
We recently found that B. subtilis performs chemotaxis to DNA. While DNA can serve as a nutrient for B. subtilis, our data suggest that the chemotaxis response is not to the DNA itself but rather to the information encoded within the DNA. Our evidence comes from experiments showing that B. subtilis prefers the DNA of more closely related species than the DNA of more distantly related ones. These results suggest that B. subtilis responds to particular DNA sequences that are enriched within the genomes of closely related bacteria. We employed the in vivo capillary assay to measure chemotaxis to DNA from different organisms. We then used SELEX-Seq to identify the specific sequences of DNA that B. subtilis responds to. The binding properties of these sequences were then evaluated using isothermal titration calorimetry (ITC) and the in vitro receptor-kinase assay. Chemotaxis to DNA is dose-dependent. Among the organisms tested, Bacilli are the preferred sources of DNA. McpC is the sole chemoreceptor for DNA. Using SELEX-Seq, we identified a number of chemotactic DNA motifs. The abundance of these motifs partially explains the organismal preference of DNA chemotaxis. While the physiological role of DNA chemotaxis is unknown, its selectivity suggests that it may be involved in horizontal gene transfer or kin selection.
Alcohols are known for their antibacterial activity. E. coli, for example, performs chemotaxis away from straight and branched alcohols. Unexpectedly, we found that B. subtilis can exhibit chemotaxis towards short-chain alcohols. Among ten chemoreceptors of B. subtilis, HemAT and McpB were found to sense alcohols. In this study, we investigated the mechanism for sensing these alcohols. In vivo chemotaxis responses were measured using the capillary assay. In vitro chemotaxis responses were measured using the kinase assay. We found that the alcohol response is dose dependent, and the kinase assays indicated that alcohol may directly interacts with chemoreceptors. Analysis of chimeric chemoreceptors revealed that the cytoplasmic domain of McpB is involved in sensing alcohols. In addition, the sensing domain of HemAT was analyzed using UV spectroscopy. UV spectroscopy suggests that alcohols do not directly bind or interact with the heme group within the HemAT sensor domain. However, Isothermal Titration Calorimetry analysis demonstrated that the cytoplasmic signaling regions of both McpB and HemAT can directly bind ethanol. Interestingly, B. subtilis does not consume alcohol. We speculate that B. subtilis may follow alcohol gradients to colonize plants or attack yeast.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2021-08-01The student, Payman Tohidifar, accepted the attached license on 2019-06-25 at 17:50.The student, Payman Tohidifar, submitted this Dissertation for approval on 2019-06-25 at 19:02.This Dissertation was approved for publication on 2019-06-26 at 12:03.DSpace SAF Submission Ingestion Package generated from Vireo submission #14082 on 2019-11-26 at 13:03:45Made available in DSpace on 2019-11-26T20:49:15Z (GMT). No. of bitstreams: 2
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Robust Distribution-Aware Ensemble Learning for Multi-Sensor Systems
No full textDetecting distribution and domain shifts is critical in decision-sensitive applications, such as industrial monitoring systems. This paper introduces a novel, robust
multi-sensor ensemble framework that integrates principles of automated machine learning (AutoML) to address the challenges of domain shifts and variability in sensor data. By
leveraging diverse model architectures, hyperparameters (HPs), and decision aggregation
strategies, the proposed framework enhances adaptability to unnoticed distribution shifts.
The method effectively handles tasks with various data properties, such as the number of
sensors, data length, and information domains. Additionally, the integration of HP optimization and model selection significantly reduces the training cost of ensemble models.
Extensive evaluations on five publicly available datasets demonstrate the effectiveness of
the proposed framework in both targeted supervised tasks and unsupervised distribution
shift detection. The proposed method significantly improves common evaluation metrics
compared to single-model baselines. Across the selected datasets, the framework achieves
near-perfect test accuracy for classification tasks, leveraging the AutoML approach. Additionally, it effectively identifies distribution shifts in the same scenarios, with an average
AUROC of 90% and an FPR95 of 20%. This study represents a practical step toward a
distribution-aware front-end approach for addressing challenges in industrial applications
under real-world scenarios using AutoML, highlighting the novelty of the method
Robust Distribution-Aware Ensemble Learning for Multi-Sensor Systems
No full textDetecting distribution and domain shifts is critical in decision-sensitive applications, such as industrial monitoring systems. This paper introduces a novel, robust multi-sensor ensemble framework that integrates principles of automated machine learning (AutoML) to address the challenges of domain shifts and variability in sensor data. By leveraging diverse model architectures, hyperparameters (HPs), and decision aggregation strategies, the proposed framework enhances adaptability to unnoticed distribution shifts. The method effectively handles tasks with various data properties, such as the number of sensors, data length, and information domains. Additionally, the integration of HP optimization and model selection significantly reduces the training cost of ensemble models. Extensive evaluations on five publicly available datasets demonstrate the effectiveness of the proposed framework in both targeted supervised tasks and unsupervised distribution shift detection. The proposed method significantly improves common evaluation metrics compared to single-model baselines. Across the selected datasets, the framework achieves near-perfect test accuracy for classification tasks, leveraging the AutoML approach. Additionally, it effectively identifies distribution shifts in the same scenarios, with an average AUROC of 90% and an FPR95 of 20%. This study represents a practical step toward a distribution-aware front-end approach for addressing challenges in industrial applications under real-world scenarios using AutoML, highlighting the novelty of the method
Domain shifts in industrial condition monitoring: a comparative analysis of automated machine learning models
No full textSelecting an appropriate model for industrial condition monitoring is challenging due to various factors. Typically, industrial datasets are small and lack statistical independence because experimental coverage of all possible operational variations is costly and sometimes practically impossible. Consequently, the resulting domain shifts pose a significant challenge. Although deep learning (DL) methods have frequently been regarded as the primary and optimal choice in many applications, they often lack major success factors in condition monitoring tasks. In this study, we benchmark the robustness of typical DL architectures against classical feature extraction and selection followed by classification (FESC) methods under domain shifts commonly encountered in industrial condition monitoring. Both DL and FESC methods are employed within an automated machine learning framework. We benchmarked these methods on seven publicly available datasets, and to simulate domain shifts, we employed leave-one-group-out validation on those datasets. Our experiments demonstrate high accuracy across all tested models for random K-fold cross-validation. However, the overall performance significantly decreases when faced with domain shifts, such as transferring the trained model from one machine to another. In four out of seven datasets, FESC methods showed better results in the presence of domain shifts. Furthermore, we also show that FESC methods are easier to interpret than DL methods. Finally, our results suggest that deep neural networks are not universally preferred over classical, low-capacity models for such tasks, as typically only a limited number of features from the input signal are needed
An essential role for MCL-1 in ATR-mediated CHK1 phosphorylation
No full textHere we report a novel role for myeloid cell leukemia 1 (Mcl-1), a Bcl-2 family member, in regulating phosphorylation and activation of DNA damage checkpoint kinase, Chk1. Increased expression of nuclear Mcl-1 and/or a previously reported short nuclear form of Mcl-1, snMcl-1, was observed in response to treatment with low concentrations of etoposide or low doses of UV irradiation. We showed that after etoposide treatment, Mcl-1 could coimmunoprecipitate with the regulatory kinase, Chk1. Chk1 is a known regulator of DNA damage response, and its phosphorylation is associated with activation of the kinase. Transient transfection with Mcl-1 resulted in an increase in the expression of phospho-Ser345 Chk1, in the absence of any evidence of DNA damage, and accumulation of cells in G2. Importantly, knockdown of Mcl-1 expression abolished Chk1 phosphorylation in response to DNA damage. Mcl-1 could induce Chk1 phosphorylation in ATM-negative (ataxia telangectasia mutated) cells, but this response was lost in ATR (AT mutated and Rad3 related)-defective cells. Low levels of UV treatment also caused transient increases in Mcl-1 levels and an ATR-dependent phosphorylation of Chk1. Together, our results strongly support an essential regulatory role for Mcl-1, perhaps acting as an adaptor protein, in controlling the ATR-mediated regulation of Chk1 phosphorylation.Peer reviewedfinal article publishe
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No full textWork was published while author was at the University of Ottawa, Physics Department, 150 Louis Pasteur, Ottawa, Ontario K1N 6N5, Canad
A proteolytic fragment of Mcl-1 exhibits nuclear localization and regulates cell growth by interaction with Cdk1
No full textMcl-1 (myeloid cell leukaemia-1) is a Bcl-2 family member with short-term pro-survival functions but whose other functions, demonstrated by embryonic lethality of knockout mice, do not involve apoptosis. In the present study, we show a cell-cycle-regulatory role of Mcl-1 involving a shortened form of the Mcl-1 polypeptide, primarily localized to the nucleus, which we call snMcl-1. snMcl-1 interacts with the cell-cycle-regulatory protein Cdk1 (cyclin-dependent kinase 1; also known as cdc2) in the nucleus, and Cdk1 bound to snMcl-1 was found to have a lower kinase activity. The interaction with Cdk1 occurs in the absence of its cyclin partners and is enhanced on treatment of cells with G2/M blocking agents, but not by G1/S blocking. The snMcl-1 polypeptide is present during S and G2 phases and is negligible in G1. Overexpression of human Mcl-1 in a murine myeloid progenitor cell line resulted in a lower rate of proliferation. Furthermore, Mcl-1-overexpressing cells had lower total Cdk1 kinase activity compared with parental cells, in both anti-Cdk1 and anti-cyclin B1 immunoprecipitates. The latter results suggest that binding to snMcl-1 alters the ability of Cdk1 to bind its conventional partner, cyclin B1. Given the important role of Cdk1 in progression through G2 and M phases, it is probable that the inhibition of Cdk1 activity accounts for the inhibitory effect of Mcl-1 on cell growth.Peer reviewedfinal article publishedCdkproteolysisnuclear localizationmyeloid cell leukaemia-1 (Mcl-1)kinasecell cycl
UAV Networks : Design Considerations
No full textThesis (Master's)--University of Washington, 2018Unmanned Aerial Vehicles have come a long way, from starting out as military reconnais- sance vehicles to a popular hobbyist’s tool. Significant research and development efforts from the commercial drone industry have significantly improved commercial UAVs and has got the wireless network and communications design community thinking about the possibility of realization and deployment of UAV networks. UAV networks, if realized, offer a significant edge over conventional wireless communication networks, they can be easily re-configured and re-arranged to handle varying traffic, can provide critical communication facilities in disaster hit regions etc. In this work, we explore the scenario where UAV air-to-ground communications between a low altitude platform such as a UAV flying happens over an open ground setting. An integral component of the above is to come up with a wireless channel model that depends more on physics rather than the empirical studies. Thus, this work develops a physics based wireless channel model for UAV air-ground link and validates the said model. This, to the best of the author’s knowledge has never been attempted before. The author then uses the validated model to look for rate-based optimization as a UAV flies right above a ground node in a straight line
Digitizing Helmes Professional Development Roadmaps
No full textKäesolev töö on ametialaste arenguplaanide digitaliseerimisest Helmeses. Helmes on\n\rrahvusvaheline tarkvaraarendus ettevõte, mis soovib tagada oma töötajatele tipptasemel\n\rametialase arengu maailmas. Selleks on Helmes välja töötanud arenguplaanid tarkvaraarendajatele. Arenguplaan sisaldab struktuursel kujul kompetentside tasemeid, taseme ootuste kirjeldusi ja soovitusi, mida, millal ja kuidas vastavaid kompetentse efektiivselt omandada.\n\r\n\rEnne käesolevat tööd oli arenguplaan Helmeses füüsilise vihikuna. Füüsilisel vihikul on\n\rmitmeid puudusi, näiteks on füüsiliste vihikute sisu uuendamine keeruline.\n\rTöö eesmärgiks on lahendada probleemid ametialase arenguplaani füüsilise vihiku kujul\n\rolemisega selliselt, et oleks võimalik luua, hallata ja arendada arenguplaane. Töö autor teostab ärianalüüsi, et tuvastada reaalne ärivajadus, analüüsib hetke olukorda ning leiab lahenduse, mis lahendab hetke probleemid ja vajadused.\n\r\n\rTöö käigus arendati veebirakendus, mis võimaldab hallata arenguplaane ja olla kursis töö-\n\rtajate ametialase arenguga. Tulemusena on kõigil Helmese spetsialistidel ajakohane arenguplaan ning töötajate ametialast arengut on võimalik paremini toetada.Current thesis is about digitizing Professional Development Roadmap in Helmes. Helmes,\n\ran international software services company, strives to have a world leading professional\n\rdevelopment for its employees. To achieve this, Helmes has implemented a Professional\n\rDevelopment Roadmap for every software developer. Professional Development Roadmap\n\ris a structured set of competence levels, expectations and recommendations of what, how\n\rand when a developer needs to improve in order to efficiently develop professionally.\n\rHelmes had the Professional Development Roadmaps in the form of physical booklets,\n\rwhich had several restrictions such as difficulties when updating its contents.\n\r\n\rThis thesis aims to solve the problems associated with a physical booklet to create, maintain and develop Professional Development Roadmaps. The author applied business analysis for identifying the underlying business needs, analyse the current situation and finally, select and implement a solution that addresses the current needs and problems.\n\r\n\rThe problems were solved by developing a web application which enables to manage Professional Development Roadmaps and keep track on the employees’ Professional Development Roadmaps. In result, Helmes specialists have latest version of Professional Development Roadmap and it is better to support employees’ professional development
